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Automatic Classification of Liver Diseases from Ultrasound Images Using GLRLM Texture Features

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Soft Computing Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 195))

Abstract

Ultrasound imaging is considered to be one of the most cost-effective and non-invasive techniques for conclusive diagnosis in some cases and preliminary diagnosis in others. Automatic liver tissue characterization and classification from ultrasonic scans have been for long, the concern of many researchers, and has been made possible today by the availability of the most powerful and cost effective computing facilities. Automatic diagnosis and classification systems are used both for quick and accurate diagnosis and as a second opinion tool for clarifications. This paper analyzes the effect of various linear, non linear and diffusion filters in improving the quality of the liver ultrasound images before proceeding to the subsequent phases of feature extraction and classification using Gray Level Run Length Matrix Features and Support Vector Machines respectively.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Amrita Vishwa Vidyapeetham, Amrita Nagar, Coimbatore, 641 112, Tamilnadu, India

    K. Raghesh Krishnan

  2. Department of Electronics and Communication Engineering, Dr. Mahalingam College of Engineering and Technology, Udumalai Road, Pollachi, 642 003, Tamilnadu, India

    R. Sudhakar

Authors
  1. K. Raghesh Krishnan
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  2. R. Sudhakar
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Corresponding author

Correspondence to K. Raghesh Krishnan .

Editor information

Editors and Affiliations

  1. , Department of Automation & Applied Infor, Aurel Vlaicu University of Arad, Blvd. Revolutiei 77, Arad, 310130, Romania

    Valentina Emilia Balas

  2. , Institute of Intelligent Engineering, Óbuda University, Bécsi út 96/b, Budapest, 1034, Hungary

    János Fodor

  3. Dept. Measurement &, Information Systems, Technical University Budapest, Magyar tudósok körutja 2, Budapest, 1521, Hungary

    Annamária R. Várkonyi-Kóczy

  4. , Department of Informatics, University of Szeged, Arpad ter 2., Szeged, 6720, Hungary

    Joszef Dombi

  5. , School of Electrical and Information, University of South Australia, 5095, Adelaide, Australia

    Lakhmi C. Jain

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Raghesh Krishnan, K., Sudhakar, R. (2013). Automatic Classification of Liver Diseases from Ultrasound Images Using GLRLM Texture Features. In: Balas, V., Fodor, J., Várkonyi-Kóczy, A., Dombi, J., Jain, L. (eds) Soft Computing Applications. Advances in Intelligent Systems and Computing, vol 195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33941-7_54

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  • DOI: https://doi.org/10.1007/978-3-642-33941-7_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33940-0

  • Online ISBN: 978-3-642-33941-7

  • eBook Packages: EngineeringEngineering (R0)

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